STUDYING AGGREGATE FORMATION BY AMYOTROPHIC LATERAL SCLEROSIS-ASSOCIATED MUTANT SOD1 PROTEIN IN DROSOPHILA MODEL

A common pathological hallmark of most neurodegenerative disorders is the presence of protein aggregates in the brain. Understanding the regulation of aggregate formation is thus important for elucidating disease pathogenic mechanisms and finding effective preventive avenues and cures. Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a selective neurodegenerative disorder predominantly affecting motor neurons. The majority of ALS cases are sporadic, however, mutations in superoxide dismutase 1 (SOD1) are responsible for about 20% of familial ALS (fALS). Mutated SOD1 proteins are prone to misfold and form protein aggregates, thus representing a good candidate for studying aggregate formation. The long-term goal of this project is to identify regulators of aggregate formation by mutant SOD1 and other ALS-associated disease proteins. The specific aim of this thesis project is to assess the possibility of using the well-established Drosophila model system to study aggregation by human SOD1 (hSOD1) mutants. To this end, using wild type and the three mutant hSOD1 (A4V, G85R and G93A) most commonly found among fALS, I have generated 16 different SOD1 constructs containing either eGFP or mCherry in-frame fluorescent reporters, established and tested both cell- and animal-based Drosophila hSOD1 models. The experimental strategy allows for clear visualization of ectopic hSOD1 expression as well as versatile co-expression schemes to fully investigate protein aggregation specifically by mutant hSOD1. I have performed pilot cell-transfection experiments and verified induced expression of hSOD1 proteins. Using several tissue- or cell type-specific Gal4 lines, I have confirmed the proper expression of hSOD1 from established transgenic fly lines. Interestingly, in both Drosophila S2 cells and different fly tissues including the eye and motor neurons, robust aggregate formation by either wild type or mutant hSOD1 proteins was not observed. These preliminary observations suggest that Drosophila might not be a good experimental organism to study aggregation and toxicity of mutant hSOD1 protein. Nevertheless this preliminary conclusion implies the potential existence of a potent protective mechanism against mutant hSOD1 aggregation and toxicity in Drosophila. Thus, results from my SOD1-ALS project in Drosophila will help future studies on how to best employ this classic model organism to study ALS and other human brain degenerative diseases.

Use of Echogenic Immunoliposomes for Delivery of both Drug and Stem Cells for Inhibition of Atheroma Progression

Use of Echogenic Immunoliposomes for Delivery of both Drug and Stem Cells for Inhibition of Atheroma Progression By Ali K. Naji B.S. Advisor: Dr. Melvin E. Klegerman PhD Background and significance: Echogenic liposomes can be used as drug and cell delivery vehicles that reduce atheroma progression. Vascular endothelial growth factor (VEGF) is a signal protein that induces vasculogenesis and angiogenesis. VEGF functionally induces migration and proliferation of endothelial cells and increases intracellular vascular permeability. VEGF activates angiogenic transduction factors through VEGF tyrosine kinase domains in high-affinity receptors of endothelial cells. Bevacizumab is a humanized monoclonal antibody specific for VEGF-A which was developed as an anti-tumor agent. Often, anti-VEGF agents result in regression of existing microvessels, inhibiting tumor growth and possibly causing tumor shrinkage with time. During atheroma progression neovasculation in the arterial adventitia is mediated by VEGF. Therefore, bevacizumab may be effective in inhibiting atheroma progression. Stem cells show an ability to inhibit atheroma progression. We have previously demonstrated that monocyte derived CD-34+ stem cells that can be delivered to atheroma by bifunctional-ELIP ( BF-ELIP) targeted to Intercellular Adhesion Molecule-1 (ICAM-1) and CD-34. Adhesion molecules such as ICAM-1 and vascular cell adhesion molecule-1 (VCAM-1) are expressed by endothelial cells under inflammatory conditions. Ultrasound enhanced liposomal targeting provides a method for stem cell delivery into atheroma and encapsulated drug release. This project is designed to examine the ability of echogenic liposomes to deliver bevacizumab and stem cells to inhibit atheroma progression and neovasculation with and without ultrasound in vitro and optimize the ultrasound parameters for delivery of bevacizumab and stem cells to atheroma. V Hypotheses: Previous studies showed that endothelial cell VEGF expression may relate to atherosclerosis progression and atheroma formation in the cardiovascular system. Bevacizumab-loaded ELIP will inhibit endothelial cell VEGF expression in vitro. Bevacizumab activity can be enhanced by pulsed Doppler ultrasound treatment of BEV-ELIP. I will also test the hypothesis that the transwell culture system can serve as an in vitro model for study of US-enhanced targeted delivery of stem cells to atheroma. Monocyte preparations will serve as a source of CD34+ stem cells. Specific Aims: Induce VEGF expression using PKA and PKC activation factors to endothelial cell cultures and use western blot and ELISA techniques to detect the expressed VEGF.  Characterize the relationship between endothelial cell proliferation and VEGF expression to develop a specific EC culture based system to demonstrate BEV-ELIP activity as an anti-VEGF agent. Design a cell-based assay for in vitro assessment of ultrasound-enhanced bevacizumab release from echogenic liposomes.  Demonstrate ultrasound delivery enhancement of stem cells by applying different types of liposomes on transwell EC culture using fluorescently labeled monocytes and detect the effect on migration and attachment rate of these echogenic liposomes with and without ultrasound in vitro.

Development of HIF-1α/HIF-1β heterodimerization inhibitors using a novel bioluminescence reporter assay system for in vitro high throughput screening and in vivo imaging

Tumor growth often outpaces its vascularization, leading to development of a hypoxic tumor microenvironment. In response, an intracellular hypoxia survival pathway is initiated by heterodimerization of hypoxia-inducible factor (HIF)-1α and HIF-1β, which subsequently upregulates the expression of several hypoxia-inducible genes, promotes cell survival and stimulates angiogenesis in the oxygen-deprived environment. Hypoxic tumor regions are often associated with resistance to various classes of radio- or chemotherapeutic agents. Therefore, development of HIF-1α/β heterodimerization inhibitors may provide a novel approach to anti-cancer therapy. To this end, a novel approach for imaging HIF-1α/β heterodimerization in vitro and in vivo was developed in this study. Using this screening platform, we identified a promising lead candidate and further chemically derivatized the lead candidate to assess the structure-activity relationship (SAR). The most effective first generation drug inhibitors were selected and their pharmacodynamics and anti-tumor efficacy in vivo were verified by bioluminescence imaging (BLI) of HIF-1α/β heterodimerization in the xenograft tumor model. Furthermore, the first generation drug inhibitors, M-TMCP and D-TMCP, demonstrated efficacy as monotherapies, resulting in tumor growth inhibition via disruption of HIF-1 signaling-mediated tumor stromal neoangiogenesis.

Development and implementation of a dynamic heterogeneous proton equivalent anthropomorphic thorax phantom for the assessment of scanned proton beam therapy

DEVELOPMENT AND IMPLEMENTATION OF A DYNAMIC HETEROGENEOUS PROTON EQUIVALENT ANTHROPOMORPHIC THORAX PHANTOM FOR THE ASSESSMENT OF SCANNED PROTON BEAM THERAPY by James Leroy Neihart, B.S. APPROVED: ______________________________David Followill, Ph.D. ______________________________Peter Balter, Ph.D. ______________________________Narayan Sahoo, Ph.D. ______________________________Kenneth Hess, Ph.D. ______________________________Paige Summers, M.S. APPROVED: ____________________________ Dean, The University of Texas Graduate School of Biomedical Sciences at Houston DEVELOPMENT AND IMPLEMENTATION OF A DYNAMIC HETEROGENEOUS PROTON EQUIVALENT ANTHROPOMORPHIC THORAX PHANTOM FOR THE ASSESSMENT OF SCANNED PROTON BEAM THERAPY A THESIS Presented to the Faculty of The University of Texas Health Science Center at Houston andThe University of TexasMD Anderson Cancer CenterGraduate School of Biomedical Sciences in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE by James Leroy Neihart, B.S. Houston, Texas Date of Graduation August, 2013 Acknowledgments I would like to acknowledge my advisory committee members, chair David Followill, Ph.D., Peter Balter, Ph.D, Narayan Sahoo, Ph.D., Kenneth Hess, Ph.D., Paige Summers M.S. and, for their time and effort contributed to this project. I would additionally like to thank the faculty and staff at the PTC-H and the RPC who assisted in many aspects of this project. Falk Pӧnisch, Ph.D. for his breath hold proton therapy treatment expertise, Matt Palmer and Jaques Bluett for proton dosimetry assistance, Matt Kerr for verification plan assistance, Carrie Amador, Nadia Hernandez, Trang Nguyen, Andrea Molineu, Lynda McDonald for TLD and film dosimetry assistance. Finally, I would like to thank my wife and family for their support and encouragement during my research and studies. Development and implementation of a dynamic heterogeneous proton equivalent anthropomorphic thorax phantom for the assessment of scanned proton beam therapy By: James Leroy Neihart, B.S. Chair of Advisory Committee: David Followill, Ph.D Proton therapy has been gaining ground recently in radiation oncology. To date, the most successful utilization of proton therapy is in head and neck cases as well as prostate cases. These tumor locations do not suffer from the resulting difficulties of treatment delivery as a result of respiratory motion. Lung tumors require either breath hold or motion tracking, neither of which have been assessed with an end-to-end phantom for proton treatments. Currently, the RPC does not have a dynamic thoracic phantom for proton therapy procedure assessment. Additionally, such a phantom could be an excellent means of assessing quality assurance of the procedures of proton therapy centers wishing to participate in clinical trials. An eventual goal of this phantom is to have a means of evaluating and auditing institutions for the ability to start clinical trials utilizing proton therapy procedures for lung cancers. Therefore, the hypothesis of this study is that a dynamic anthropomorphic thoracic phantom can be created to evaluate end-to-end proton therapy treatment procedures for lung cancer to assure agreement between the measured and calculated dose within 5% / 5 mm with a reproducibility of 2%. Multiple materials were assessed for thoracic heterogeneity equivalency. The phantom was designed from the materials found to be in greatest agreement. The phantom was treated in an end-to-end treatment four times, which included simulation, treatment planning and treatment delivery. Each treatment plan was delivered three times to assess reproducibility. The dose measured within the phantom was compared to that of the treatment plan. The hypothesis was fully supported for three of the treatment plans, but failed the reproducibility requirement for the most aggressive treatment plan.

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Characterization of Jak, STAT, and Src interactions in Head and Neck Squamous Cell Carcinoma

Recurrence of Head and Neck Squamous Cell Carcinoma (HNSCC) is common; thus, it is essential to improve the effectiveness and reduce toxicity of current treatments. Proteins in the Src/Jak/STAT pathway represent potential therapeutic targets, as this pathway is hyperactive in HNSCC and it has roles in cell migration, metastasis, proliferation, survival, and angiogenesis. During short-term Src inhibition, Janus kinase (Jak) 2, and signal transducer and activator of transcription (STAT) 3 and STAT5 are dephosphorylated and inactivated. Following sustained Src inhibition, STAT5 remains inactive, but Jak2 and STAT3 are reactivated following their early inhibition. To further characterize the mechanism of this novel feedback pathway we performed several experiments to look at the interactions between Src, Jak2, STAT5 and STAT3. We attempted to develop a non-radioactive kinase assay using purified recombinant Jak2 and Src proteins, but found that phospho-tyrosine antibodies were non-specifically binding to purified recombinant proteins. We then performed in vitro kinase assays (IVKAs) using purified recombinant Jak2, Src, STAT3, and STAT5 proteins with and without Src and Jak2 pharmacologic inhibitors. We also examined the interactions of these proteins in intact HNSCC cells. We found that recombinant Jak2, STAT3, and STAT5 are direct substrates of Src and that recombinant Src, STAT3, and STAT5 are direct substrates of Jak2 in the IVKA. To our knowledge, the finding that Src is a Jak substrate is novel and has not been shown before. In intact HNSCC cells we find that STAT3 can be reactivated despite continuous Src inhibition and that STAT5 continues to be inhibited despite Jak2 reactivation. Also, Jak2 inhibition did not affect Src or STAT5 activity but it did cause STAT3 inhibition. We hypothesized that the differences between the intact cells and the IVKA assays were due to a potential need for binding partners in intact HNSCC cells. One potential binding partner that we examined is the epidermal growth factor receptor (EGFR). We found that EGFR activation caused increased activation of Src and STAT5 but not Jak2. Our results demonstrate that although STAT3 and STAT5 are capable of being Src and Jak2 substrates, in intact HNSCC cells Src predominantly regulates STAT5 and Jak2 regulates STAT3. Regulation of STAT5 by Src may involve interactions between Src and EGFR. This knowledge along with future studies will better define the mechanisms of STAT regulation in HNSCC cells and ultimately result in an ideal combination of therapeutic agents for HNSCC.

Targeted Deletion Of Functionally Validated Enhancers Defines Their Role in Mouse Limb Development

Transcriptional enhancers are genomic DNA sequences that contain clustered transcription factor (TF) binding sites. When combinations of TFs bind to enhancer sequences they act together with basal transcriptional machinery to regulate the timing, location and quantity of gene transcription. Elucidating the genetic mechanisms responsible for differential gene expression, including the role of enhancers, during embryological and postnatal development is essential to an understanding of evolutionary processes and disease etiology. Numerous methods are in use to identify and characterize enhancers. Several high-throughput methods generate large datasets of enhancer sequences with putative roles in embryonic development. However, few enhancers have been deleted from the genome to determine their roles in the development of specific structures, such as the limb. Manipulation of enhancers at their endogenous loci, such as the deletion of such elements, leads to a better understanding of the regulatory interactions, rules and complexities that contribute to faithful and variant gene transcription – the molecular genetic substrate of evolution and disease. To understand the endogenous roles of two distinct enhancers known to be active in the mouse embryo limb bud we deleted them from the mouse genome. I hypothesized that deletion of these enhancers would lead to aberrant limb development. The enhancers were selected because of their association with p300, a protein associated with active transcription, and because the human enhancer sequences drive distinct lacZ expression patterns in limb buds of embryonic day (E) 11.5 transgenic mice. To confirm that the orthologous mouse enhancers, mouse 280 and 1442 (M280 and M1442, respectively), regulate expression in the developing limb we generated stable transgenic lines, and examined lacZ expression. In M280-lacZ mice, expression was detected in E11.5 fore- and hindlimbs in a region that corresponds to digits II-IV. M1442-lacZ mice exhibited lacZ expression in posterior and anterior margins of the fore- and hindlimbs that overlapped with digits I and V and several wrist bones. We generated mice lacking the M280 and M1442 enhancers by gene targeting. Intercrosses between M280 -/+ and M1442 -/+, respectively, generated M280 and M1442 null mice, which are born at expected Mendelian ratios and manifest no gross limb malformations. Quantitative real-time PCR of mutant E11.5 limb buds indicated that significant changes in transcriptional output of enhancer-proximal genes accompanied the deletion of both M280 and M1442. In neonatal null mice we observed that all limb bones are present in their expected positions, an observation also confirmed by histology of E18.5 distal limbs. Fine-scale measurement of E18.5 digit bone lengths found no differences between mutant and control embryos. Furthermore, when the developmental progression of cartilaginous elements was analyzed in M280 and M1442 embryos from E13.5-E15.5, transient development defects were not detected. These results demonstrate that M280 and M1442 are not required for mouse limb development. Though M280 is not required for embryonic limb development it is required for the development and/or maintenance of body size – adult M280 mice are significantly smaller than control littermates. These studies highlight the importance of experiments that manipulate enhancers in situ to understand their contribution to development.

THE MOLECULAR INTERACTION BETWEEN TYPE II DIABETES AND ALZHEIMER’S DISEASE THROUGH CROSS-SEEDING OF PROTEIN MISFOLDING

With the population of the world aging, the prominence of diseases such as Type II Diabetes (T2D) and Alzheimer’s disease (AD) are on the rise. In addition, patients with T2D have an increased risk of developing AD compared to age-matched individuals, and the number of AD patients with T2D is higher than among aged-matched non-AD patients. AD is a chronic and progressive dementia characterized by amyloid-beta (Aβ) plaques, neurofibrillary tangles (NFTs), neuronal loss, brain inflammation, and cognitive impairment. T2D involves the dysfunctional use of pancreatic insulin by the body resulting in insulin resistance, hyperglycemia, hyperinsulinemia, pancreatic beta cell (β-cell) death, and other complications. T2D and AD are considered protein misfolding disorders (PMDs). PMDs are characterized by the presence of misfolded protein aggregates, such as in T2D pancreas (islet amyloid polypeptide - IAPP) and in AD brain (amyloid– Aβ) of affected individuals. The misfolding and accumulation of these proteins follows a seeding-nucleation model where misfolded soluble oligomers act as nuclei to propagate misfolding by recruiting other native proteins. Cross-seeding occurs when oligomers composed by one protein seed the aggregation of a different protein. Our hypothesis is that the pathological interactions between T2D and AD may in part occur through cross-seeding of protein misfolding. To test this hypothesis, we examined how each respective aggregate (Aβ or IAPP) affects the disparate disease pathology through in vitro and in vivo studies. Assaying Aβ aggregates influence on T2D pathology, IAPP+/+/APPSwe+/- double transgenic (DTg) mice exhibited exacerbated T2D-like pathology as seen in elevated hyperglycemia compared to controls; in addition, IAPP levels in the pancreas are highest compared to controls. Moreover, IAPP+/+/APPSwe+/- animals demonstrate abundant plaque formation and greater plaque density in cortical and hippocampal areas in comparison to controls. Indeed, IAPP+/+/APPSwe+/- exhibit a colocalization of both misfolded proteins in cerebral plaques suggesting IAPP may directly interact with Aβ and aggravate AD pathology. In conclusion, these studies suggest that cross-seeding between IAPP and Aβ may occur, and that these protein aggregates exacerbate and accelerate disease pathology, respectively. Further mechanistic studies are necessary to determine how these two proteins interact and aggravate both pancreatic and brain pathologies.

Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

The Role of K63-linked Ubiquitination Cycles in Akt Kinase Activation

Akt (also known as protein kinase B) serves a central regulator in PI3K/Akt signaling pathways to regulate numerous physiological functions including cell proliferation, survival and metabolism. Akt activation requires the binding of Akt to phospholipid PIP3 on the plasma membrane and subsequent phosphorylation of Akt by its kinases. Growth factor-mediated membrane recruitment of Akt is a crucial step for Akt activation. However, the mechanism of Akt membrane translocation is unclear. Protein ubiquitination is a significant posttranslational modification that controls many biological functions such as protein trafficking and signaling activation. Therefore, we hypothesize that ubiquitination may be involved in Akt signaling activation. We have demonstrated that Akt could be conjugated with non-proteolytic K63-linked ubiquitination by TRAF6 ubiquitin E3 ligase. This modification on Akt was required for membrane recruitment, phosphorylation and activation of Akt in response to growth factor stimulation. The human cancer-associated Akt E17K mutant exhibited an increase in K63-linked ubiquitination, which contributes to the enrichment of membrane recruitment and phosphorylation of Akt. Thus, we conclude that K63-linked ubiquitination is a critical step for oncogenic Akt activation and also involved in human cancer development. Notably, the process of protein ubiquitination can be reversed by deubiquitinating enzymes (DUBs), which play a critical role to terminate signaling activation induced by ubiquitination. To further investigate how ubiquitination cycles regulate Akt activation, we have identified that CYLD as a DUB for Akt, and CYLD inhibited growth factor-induced ubiquitination and activation of Akt. Under serum-depletion condition, CYLD interacts with Akt and keep Akt under inactive state by directly removing K63-linked ubiquitination of Akt. CYLD disassociates with Akt upon growth factor stimulation, thereby allowing E3 ligases to induce ubiquitination and activation of Akt. We also demonstrated that CYLD deficiency promoted cancer cell proliferation, survival, glucose metabolism and human prostate cancer development. Therefore, we conclude that CYLD plays a critical role for negatively regulating Akt signaling activation through deubiquitination of Akt. In summary, this study delineated the important mechanism of cycles of ubiquitination and deubiquitination of Akt in regulating membrane translocation and activation of Akt, and TRAF6 and CYLD as central switches for these processes.

A Genomic Approach to Identify The Notch Pathway as a Putative Tumor Suppressor in Endometrial Cancer

Endometrial cancer is the most common gynecological malignancy and the fourth most frequently diagnosed cancer among women. The molecular changes that distinguish normal endometrium from endometrial carcinoma are not thoroughly understood. Identification of these changes could potentially aid in identifying at-risk women who are especially prone to develop endometrial cancer, such as obese women and women with Lynch Syndrome. A microarray analysis was performed using normal endometrium from thin and obese women and cancerous endometrium from obese women. We validated the differential expression of ten genes whose expression was significantly up-regulated or down-regulated using qRT-PCR. All of the genes had distinct expression levels depending on the endometrial carcinoma histotype. As a result, they could serve as molecular markers to distinguish between normal endometrium and endometrial cancer, as well as between low grade endometrial carcinomas and high grade endometrial carcinomas. Two of the ten genes validated, HEYL and HES1, are down-stream targets of the Notch signaling pathway. HEYL and HES1 were identified by microarray and qRT-PCR to have a significant decrease in expression in endometrial carcinomas compared to normal endometrium. We further analyzed the differential expression of other components of the Notch signaling pathway, Notch4 and Jagged1. They were also identified by qRT-PCR to be significantly down-regulated in endometrial carcinomas compared to normal endometrium. Therefore, we believe the Notch signaling pathway to act as a tumor suppressor in endometrial carcinomas.

Evaluation of PRESAGE® dosimeters for brachytherapy sources and the 3D dosimetry and characterization of the new AgX100 125I seed model

With continuous new improvements in brachytherapy source designs and techniques, method of 3D dosimetry for treatment dose verifications would better ensure accurate patient radiotherapy treatment. This study was aimed to first evaluate the 3D dose distributions of the low-dose rate (LDR) Amersham 6711 OncoseedTM using PRESAGE® dosimeters to establish PRESAGE® as a suitable brachytherapy dosimeter. The new AgX100 125I seed model (Theragenics Corporation) was then characterized using PRESAGE® following the TG-43 protocol. PRESAGE® dosimeters are solid, polyurethane-based, 3D dosimeters doped with radiochromic leuco dyes that produce a linear optical density response to radiation dose. For this project, the radiochromic response in PRESAGE® was captured using optical-CT scanning (632 nm) and the final 3D dose matrix was reconstructed using the MATLAB software. An Amersham 6711 seed with an air-kerma strength of approximately 9 U was used to irradiate two dosimeters to 2 Gy and 11 Gy at 1 cm to evaluate dose rates in the r=1 cm to r=5 cm region. The dosimetry parameters were compared to the values published in the updated AAPM Report No. 51 (TG-43U1). An AgX100 seed with an air-kerma strength of about 6 U was used to irradiate two dosimeters to 3.6 Gy and 12.5 Gy at 1 cm. The dosimetry parameters for the AgX100 were compared to the values measured from previous Monte-Carlo and experimental studies. In general, the measured dose rate constant, anisotropy function, and radial dose function for the Amersham 6711 showed agreements better than 5% compared to consensus values in the r=1 to r=3 cm region. The dose rates and radial dose functions measured for the AgX100 agreed with the MCNPX and TLD-measured values within 3% in the r=1 to r=3 cm region. The measured anisotropy function in PRESAGE® showed relative differences of up to 9% with the MCNPX calculated values. It was determined that post-irradiation optical density change over several days was non-linear in different dose regions, and therefore the dose values in the r=4 to r=5 cm regions had higher uncertainty due to this effect. This study demonstrated that within the radial distance of 3 cm, brachytherapy dosimetry in PRESAGE® can be accurate within 5% as long as irradiation times are within 48 hours.

Induction of synthetic lethality in mutant KRAS cells for non-small cell lung cancers chemoprevention and therapy

Lung cancer is the leading cause of cancer death in both men and women in the United States and worldwide. Despite improvement in treatment strategies, the 5-year survival rate of lung cancer patients remains low. Thus, effective chemoprevention and treatment approaches are sorely needed. Mutations and activation of KRAS occur frequently in tobacco users and the early stage of development of non-small cell lung cancers (NSCLC). So they are thought to be the primary driver for lung carcinogenesis. My work showed that KRAS mutations and activations modulated the expression of TNF-related apoptosis-inducing ligand (TRAIL) receptors by up-regulating death receptors and down-regulating decoy receptors. In addition, we showed that KRAS suppresses cellular FADD-like IL-1β-converting enzyme (FLICE)-like inhibitory protein (c-FLIP) expression through activation of ERK/MAPK-mediated activation of c-MYC which means the mutant KRAS cells could be specifically targeted via TRAIL induced apoptosis. The expression level of Inhibitors of Apoptosis Proteins (IAPs) in mutant KRAS cells is usually high which could be overcome by the second mitochondria-derived activator of caspases (Smac) mimetic. So the combination of TRAIL and Smac mimetic induced the synthetic lethal reaction specifically in the mutant-KRAS cells but not in normal lung cells and wild-type KRAS lung cancer cells. Therefore, a synthetic lethal interaction among TRAIL, Smac mimetic and KRAS mutations could be used as an approach for chemoprevention and treatment of NSCLC with KRAS mutations. Further data in animal experiments showed that short-term, intermittent treatment with TRAIL and Smac mimetic induced apoptosis in mutant KRAS cells and reduced tumor burden in a KRAS-induced pre-malignancy model and mutant KRAS NSCLC xenograft models. These results show the great potential benefit of a selective therapeutic approach for the chemoprevention and treatment of NSCLC with KRAS mutations.

AN EVALUATION OF THE CONSISTENCY OF IMRT PATIENT-SPECIFIC QA TECHNIQUES

To ensure the integrity of an intensity modulated radiation therapy (IMRT) treatment, each plan must be validated through a measurement-based quality assurance (QA) procedure, known as patient specific IMRT QA. Many methods of measurement and analysis have evolved for this QA. There is not a standard among clinical institutions, and many devices and action levels are used. Since the acceptance criteria determines if the dosimetric tools’ output passes the patient plan, it is important to see how these parameters influence the performance of the QA device. While analyzing the results of IMRT QA, it is important to understand the variability in the measurements. Due to the different form factors of the many QA methods, this reproducibility can be device dependent. These questions of patient-specific IMRT QA reproducibility and performance were investigated across five dosimeter systems: a helical diode array, radiographic film, ion chamber, diode array (AP field-by-field, AP composite, and rotational composite), and an in-house designed multiple ion chamber phantom. The reproducibility was gauged for each device by comparing the coefficients of variation (CV) across six patient plans. The performance of each device was determined by comparing each one’s ability to accurately label a plan as acceptable or unacceptable compared to a gold standard. All methods demonstrated a CV of less than 4%. Film proved to have the highest variability in QA measurement, likely due to the high level of user involvement in the readout and analysis. This is further shown by how the setup contributed more variation than the readout and analysis for all of the methods, except film. When evaluated for ability to correctly label acceptable and unacceptable plans, two distinct performance groups emerged with the helical diode array, AP composite diode array, film, and ion chamber in the better group; and the rotational composite and AP field-by-field diode array in the poorer group. Additionally, optimal threshold cutoffs were determined for each of the dosimetry systems. These findings, combined with practical considerations for factors such as labor and cost, can aid a clinic in its choice of an effective and safe patient-specific IMRT QA implementation.